Model Prediksi Kelulusan Mahasiswa Menggunakan Decision Tree C4.5 dan Software Weka

In this research, we build a model to predict graduation status of students in Institut Bisnis dan Informatika Kesatuan using C4.5 decision tree algorithm. The prediction model is built using students’ GPA from semester 1 to semester 4, for students with admission year of 2013 to 2016. The prediction model obtained is a decision tree with 26 rules, with the attribute IPS_4 being the attribute that determines the graduation label of students. This prediction model yields an accuracy of 73%, a result that is not good enough. This result is probably due to unbalanced proportion of the data used.